Experiment
Yeast as background and USP2 proteins spiked in different concentration. This Experiment is designed for DIA benchmarking of different workflow using DIA-NN.
Import data
Reading DIA data from data/report.tsv using Precursor.Translated intensities from DIA-NN.
All the precursors with Q-value < 0.01 are used for the analysis.
Creating Q-Features object and run pre processing
The pre- processing steps are:
- Filtering precursor with more than 3 samples with no missing intensities across all the samples
- Select only proteotypic peptides
- Select proteins with at least 3 peptides
Data Missing Analysis
Normalization
Raw intensities from DIA-NN are processed as follow:
- Log 2 transformed
- Normalized across all the samples using quantiles method
- Summarization at protein level using **** function
PCA
DE Analysis
Using MSqRob2.
GroupA GroupB GroupC GroupD GroupE
15.13545 14.78455 14.88787 15.01882 15.01860 QC plots
Group Comparison
Differential Expressed Proteins [1] “B” “A”
Differential Expressed Proteins [1] “D” “A”
Session Info
R version 4.3.3 (2024-02-29 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)
Matrix products: default
locale:
[1] LC_COLLATE=English_Belgium.utf8 LC_CTYPE=English_Belgium.utf8
[3] LC_MONETARY=English_Belgium.utf8 LC_NUMERIC=C
[5] LC_TIME=English_Belgium.utf8
time zone: Europe/Brussels
tzcode source: internal
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] pheatmap_1.0.12 biomaRt_2.58.2
[3] gridExtra_2.3 ggVennDiagram_1.5.2
[5] hrbrthemes_0.8.7 factoextra_1.0.7
[7] MSnbase_2.28.1 ProtGenerics_1.34.0
[9] mzR_2.36.0 Rcpp_1.0.12
[11] DT_0.33 plotly_4.10.4
[13] here_1.0.1 magrittr_2.0.3
[15] lubridate_1.9.3 forcats_1.0.0
[17] stringr_1.5.1 purrr_1.0.2
[19] readr_2.1.5 tidyr_1.3.1
[21] tibble_3.2.1 ggplot2_3.5.0
[23] tidyverse_2.0.0 dplyr_1.1.4
[25] visdat_0.6.0 readxl_1.4.3
[27] msqrob2_1.10.0 QFeatures_1.12.0
[29] MultiAssayExperiment_1.28.0 SummarizedExperiment_1.32.0
[31] Biobase_2.62.0 GenomicRanges_1.54.1
[33] GenomeInfoDb_1.38.8 IRanges_2.36.0
[35] S4Vectors_0.40.2 BiocGenerics_0.48.1
[37] MatrixGenerics_1.14.0 matrixStats_1.3.0
loaded via a namespace (and not attached):
[1] splines_4.3.3 later_1.3.2 bitops_1.0-7
[4] filelock_1.0.3 cellranger_1.1.0 preprocessCore_1.64.0
[7] XML_3.99-0.16.1 lifecycle_1.0.4 rstatix_0.7.2
[10] doParallel_1.0.17 rprojroot_2.0.4 lattice_0.22-6
[13] MASS_7.3-60.0.1 crosstalk_1.2.1 backports_1.4.1
[16] sass_0.4.9 limma_3.58.1 rmarkdown_2.26
[19] jquerylib_0.1.4 yaml_2.3.8 httpuv_1.6.15
[22] RColorBrewer_1.1-3 MsCoreUtils_1.14.1 DBI_1.2.2
[25] minqa_1.2.6 abind_1.4-5 zlibbioc_1.48.2
[28] AnnotationFilter_1.26.0 RCurl_1.98-1.14 rappdirs_0.3.3
[31] gdtools_0.3.7 GenomeInfoDbData_1.2.11 ggrepel_0.9.5
[34] crul_1.4.2 ncdf4_1.22 codetools_0.2-20
[37] DelayedArray_0.28.0 xml2_1.3.6 tidyselect_1.2.1
[40] farver_2.1.1 httpcode_0.3.0 lme4_1.1-35.3
[43] BiocFileCache_2.10.2 jsonlite_1.8.8 iterators_1.0.14
[46] systemfonts_1.0.6 foreach_1.5.2 tools_4.3.3
[49] progress_1.2.3 glue_1.7.0 BiocBaseUtils_1.4.0
[52] Rttf2pt1_1.3.12 SparseArray_1.2.4 xfun_0.43
[55] withr_3.0.0 BiocManager_1.30.22 fastmap_1.1.1
[58] boot_1.3-30 fansi_1.0.6 digest_0.6.35
[61] timechange_0.3.0 R6_2.5.1 mime_0.12
[64] colorspace_2.1-0 RSQLite_2.3.6 utf8_1.2.4
[67] generics_0.1.3 fontLiberation_0.1.0 data.table_1.15.4
[70] prettyunits_1.2.0 httr_1.4.7 htmlwidgets_1.6.4
[73] S4Arrays_1.2.1 pkgconfig_2.0.3 gtable_0.3.4
[76] blob_1.2.4 impute_1.76.0 XVector_0.42.0
[79] htmltools_0.5.8.1 carData_3.0-5 fontBitstreamVera_0.1.1
[82] MALDIquant_1.22.2 clue_0.3-65 scales_1.3.0
[85] png_0.1-8 knitr_1.46 tzdb_0.4.0
[88] nlme_3.1-164 curl_5.2.1 nloptr_2.0.3
[91] cachem_1.0.8 parallel_4.3.3 extrafont_0.19
[94] AnnotationDbi_1.64.1 mzID_1.40.0 vsn_3.70.0
[97] pillar_1.9.0 grid_4.3.3 vctrs_0.6.5
[100] pcaMethods_1.94.0 ggpubr_0.6.0 promises_1.3.0
[103] car_3.1-2 dbplyr_2.5.0 xtable_1.8-4
[106] cluster_2.1.6 extrafontdb_1.0 evaluate_0.23
[109] cli_3.6.2 compiler_4.3.3 rlang_1.1.3
[112] crayon_1.5.2 ggsignif_0.6.4 labeling_0.4.3
[115] affy_1.80.0 plyr_1.8.9 stringi_1.8.3
[118] viridisLite_0.4.2 BiocParallel_1.36.0 munsell_0.5.1
[121] Biostrings_2.70.3 lazyeval_0.2.2 fontquiver_0.2.1
[124] Matrix_1.6-5 hms_1.1.3 bit64_4.0.5
[127] gfonts_0.2.0 KEGGREST_1.42.0 statmod_1.5.0
[130] shiny_1.8.1.1 broom_1.0.5 igraph_2.0.3
[133] memoise_2.0.1 bslib_0.7.0 affyio_1.72.0
[136] bit_4.0.5